Bibliographic record
Abstract
Lived experience and the critical work of feminist and queer scholars across disciplines have shown that political hope—which, at face value, signals optimism about the possibility of social transformation—often disappoints due to the concealment of an underlying complicity with the status quo and its structuring violence. In the face of these failures, ought we reject hope altogether and embrace negativity and refusal, as Lee Edelman suggests in No Future? Rejecting the common binary opposition between hope and refusal, this article instead coins and proposes the practice of “hope as refusal.” To employ hope as refusal, I argue, requires rejecting inevitability in all its forms, including the naively hopeful belief that “progress” is inevitable and the complacently hopeless belief that the violence of the present is inevitable. Instead, I draw from queer women of color and Black feminisms to argue for the inseparability of refusing the world of our present and striving for the possibility of other worlds and futures that do not merely perpetuate it. I turn to Saidiya Hartman’s writings, as well as her work as a founding member of the Practicing Refusal Collective, as illuminating examples of projects shaped by hope as refusal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.113 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".